Escola Superior de Educação
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- Assessment of heart rate variability and infrared thermography in response to exercise-induced muscle damagePublication . Marques, Wanessa Karoline Brito; Santana, Paulo Vitor Albuquerque; Oliveira, Vinícius Fernandes Ferreira de; Pussieldi, Guilherme de Azambuja; Leite, Luciano Bernardes; Forte, Pedro; Assis, Miller Gomes; Pimenta, Eduardo Mendonça; Mostarda, Cristiano Teixeira; Costa, Herikson Araújo; Dibai-Filho, Almir Vieira; Oliveira Junior, Mario Norberto Sevilio; Cabido, Christian Emmanuel Torres; Veneroso, Christiano EduardoThe aim of this study is to investigate the behavior of autonomic nervous activation and infrared thermography (IR) after an eccentric exercise protocol. The sample consisted of ten physically active men (22.5 ± 3.3 years) who had not practiced plyometric training in the 6 months prior to the study. After a period of familiarization and assessment of body composition, the participants underwent a plyometric jumping protocol, including jumps over a 50 cm obstacle and jumps from a 50 cm box, after a 5-min warm-up on the treadmill. Subsequently, the following assessments were performed: assessments included measures of rating perceived fatigue (RPF), delayed-onset muscle soreness (DOMS), IRT and heart rate variability (HRV) performed at 24, 48 and 72 h after exercise. The RPF results showed a significant increase from baseline at 24 h, 48 h, and 72 h after the muscle damage protocol. For DOMS, significant increases were observed at 24 h, 48 h, and 72 h compared to baseline, with values notably higher at 24 h and 48 h than at 72 h. Thermographic assessments of the posterior thigh region showed a higher concentration of pixels in the warm zone at 48 h and 72 h compared to baseline, as well as at 48 h and 72 h compared to 24 h. Regarding HRV, the LF/HF ratio and %LF were elevated at 24 h and 48 h compared to baseline and 72 h, while %HF decreased at 24 h and 48 h relative to baseline. The exercise-induced stress increased warm-zone pixels and elevated sympathetic activity (LF/HF ratio and %LF) up to 48 h post-exercise. This was followed by a shift to increased parasympathetic modulation (higher %HF), indicating recovery. These findings underscore the utility of IRT and HRV in monitoring recovery and optimizing training.
- Relationship Between Quality of Life, Level of Physical Activity, Physical Fitness, and Body Composition on the Academic Performance of High School Students in an Integrated Educational SystemPublication . Gazolla, Jeann C.; Ferreira-Júnior, João; Encarnação, Samuel; Schneider, André; Monteiro, António M.; Teixeira, José Eduardo; Forte, Pedro; Oliveira, João P.; Borba, Diego; Costa, Carlos Manuel Azevedo; Vieira, Carlos A.Adolescence is a critical period for the development of physical and cognitive health. Understanding how lifestyle and physical health parameters relate to academic performance and quality of life may inform school-based interventions. Purpose: This study aimed to evaluate the relationship between physical activity level (PAL), quality of life (QoL), physical fitness (PF), strength, speed and agility, body composition, and academic performance (AP) in high school students. Research Design: A cross-sectional, correlational study using multiple linear regression models to assess predictive relationships. Study Sample: 365 students (aged 16.93 ± 0.94 years) participated in the study. Data Collection and Analysis: Evaluations included Body Mass Index (BMI); PAL; QoL; PF (handgrip strength, countermovement vertical jump, and agility); and AP. A multiple linear regression was conducted using AP as the dependent variable, with BMI, jump performance, agility, handgrip strength, and PAL scores as predictors. Five additional multiple linear regressions were performed, each with a QoL domain as the dependent variable, and the same set of predictors as in the AP model. Participants’ age and sex were included as covariates in all models. Results: Significant predictive capacity was observed for AP (F = 2.22, p = .028, R = 0.31, R2 = 0.093) and two QoL domains: physical health (F = 2.32, p = .021, R = 0.28, R2 = 0.079) and psychological health (F = 2.32 and p = .021, R = 0.28, R2 = 0.079); however, with weak correlation coefficients (0.2 ≤ R <0.4). Only jump performance and age significantly affected the AP model (β = 0.038, p = .014) and the psychological health domain model (β = 0.48, p = .018). Conclusions: The predictors explained 9.3% of the variance in AP and 7.9% of the variance in physical health and psychological health in QoL domains, suggesting that additional factors (e.g., socioeconomic status, dietary habits) may play a role. The findings highlight the importance of multifactorial approaches in future research.